Articles
All vignettes
- Convolutional autoencoder for image denoising
How to train a deep convolutional autoencoder for image denoising.
- Customizing what happens in `fit()` with TensorFlow
Overriding the training step of the Model class with TensorFlow.
- Multi-GPU distributed training with TensorFlow
Guide to multi-GPU training for Keras models with TensorFlow.
- Distributed training with Keras 3
Complete guide to the distribution API for multi-backend Keras.
- The Functional API
Complete guide to the functional API.
- Getting Started with Keras
- Imbalanced classification: credit card fraud detection
Demonstration of how to handle highly imbalanced classification problems.
- Keras examples
- Introduction to Keras for engineers
First contact with Keras 3.
- Introduction to Keras for Researchers
Everything you need to know to use Keras & TensorFlow for deep learning research.
- Making new layers and models via subclassing
Complete guide to writing
LayerandModelobjects from scratch.- Simple MNIST convnet
A simple convnet that achieves ~99% test accuracy on MNIST.
- Train a Siamese MLP on pairs of digits from the MNIST dataset.
- English-to-Spanish translation with a sequence-to-sequence Transformer
Implementing a sequence-to-sequence Transformer and training it on a machine translation task.
- Image segmentation with a U-Net-like architecture
Image segmentation model trained from scratch on the Oxford Pets dataset.
- The Sequential model
Complete guide to the Sequential model.
- Save, serialize, and export models
Complete guide to saving, serializing, and exporting models.
- Structured data classification with FeatureSpace
Classify tabular data in a few lines of code.
- Text classification from scratch
Text sentiment classification starting from raw text files.
- Timeseries anomaly detection using an Autoencoder
Detect anomalies in a timeseries using an Autoencoder.
- Timeseries classification from scratch
Training a timeseries classifier from scratch on the FordA dataset from the UCR/UEA archive.
- Training & evaluation with the built-in methods
Complete guide to training & evaluation with
fit()andevaluate().- Transfer learning & fine-tuning
Complete guide to transfer learning & fine-tuning in Keras.
- Understanding masking & padding
Complete guide to using mask-aware sequence layers in Keras.
- Writing a training loop from scratch in TensorFlow
Complete guide to writing low-level training & evaluation loops in TensorFlow.
- Writing your own callbacks
Complete guide to writing new Keras callbacks.